Performance of different CT enhancement quantification methods as predictors of pancreatic cancer recurrence after upfront surgery

The prognosis of pancreatic cancer (PDAC) after tumor resection remains poor, mostly due to a high but variable risk of recurrence. A promising tool for improved prognostication is the quantification of CT tumor enhancement. For this, various enhancement formulas have been used in previous studies. However, a systematic comparison of these formulas is lacking. In the present study, we applied twenty-three previously published CT enhancement formulas to our cohort of 92 PDAC patients who underwent upfront surgery. We identified seven formulas that could reliably predict tumor recurrence. Using these formulas, weak tumor enhancement was associated with tumor recurrence at one and two years after surgery (p ≤ 0.030). Enhancement was inversely associated with adverse clinicopathological features. Low enhancement values were predictive of a high recurrence risk (Hazard Ratio ≥ 1.659, p ≤ 0.028, Cox regression) and a short time to recurrence (TTR) (p ≤ 0.027, log-rank test). Some formulas were independent predictors of TTR in multivariate models. Strikingly, almost all of the best-performing formulas measure solely tumor tissue, suggesting that normalization to non-tumor structures might be unnecessary. Among the top performers were also the absolute arterial/portal venous tumor attenuation values. These can be easily implemented in clinical practice for better recurrence prediction, thus potentially improving patient management.

15 patients showed no signs of tumor recurrence after a follow-up time of 843-3501 days, median 1660 (IQR 1085-2521) days.

Placement of regions of interest and extraction of attenuation values
Attenuation values for every CT phase (non-contrast, late arterial, portal venous) were extracted from the following regions of interest (ROIs): tumor (covering a relevant proportion of the tumor area, with a margin of at least 2 mm to the border of the tumor, n = 92); tumor periphery (n = 92); upstream parenchyma (best measurable area, n = 72); upstream parenchyma (border to the tumor, n = 72); downstream parenchyma (best measurable area, n = 45); aorta (n = 92).For more details on ROI placement see the Materials and Methods section, the Supplementary materials (page 4) and Fig. 1.

Extraction of CT enhancement measurements/formulas from previous studies
Using a PubMed ® MEDLINE and PubMed Central ® search, sixteen PDAC studies were identified that used CT enhancement measurements of PDAC for prediction of patient prognosis or of prognostically relevant histopathological tumor features between 01/2009 and 01/2024.

Comparison of attenuation values from regions on interest
Attenuation values from the ROIs are summarized in the Supplementary Materials (page 7), including Supplementary Table 2.
The results from the univariate Cox regression analyses with enhancement measurement as predictor variables are presented in Table 2.
A comparison of clinicopathological parameters and enhancement parameters (with p < 0.05) between patients without and with tumor recurrence at 1 year is presented in Table 1.

Discussion
The present exploratory study identifies seven CT enhancement formulas that could reliably predict tumor recurrence in PDAC after upfront surgery.According to these formulas ((1), ( 2), ( 3), ( 4), ( 6), (8), and ( 13)), locoregional or distant tumor recurrence at one and two years after surgery was associated with weak tumor enhancement.Enhancement values from some of these formulas were correlated with adverse clinicopathological features such as histopathological grading, the presence of lymph node metastases, and serum CA19-9.Low CT enhancement values from these formulas were predictive of short time to recurrence (TTR) in univariate Kaplan-Meier analyses and a high tumor recurrence risk in univariate Cox regression analyses.(1), ( 2), (3), and (13) were the best-performing formulas in univariate analysis, and out of these, (3) and ( 13) were independent predictors of TTR in a Cox regression model incorporating the clinicopathological features T stage, N status, histopathological grading, and CA 19-9.
Strikingly, six out of the seven best-performing formulas measure solely tumor tissue without any normalization to non-tumor structures.However, the formula with the best predictive ability for tumor recurrence was formula ( 13) from a study by Torphy et al. 13 .The formula normalizes the tumor enhancement to the aortic enhancement in the arterial phase.In the original study by Torphy et al., the formula was also used to predict TTR as in the present study.However, in their study, this formula was outperformed by the equivalent formula for the portal venous phase 13 .
Notably, in our study, simple absolute attenuation measurements of the tumor in the late arterial (1) and portal venous phase (2) were also among the best prognostic factors on our heterogeneous CT dataset.This could mean that normalization of PDAC attenuation values to non-tumor structures for minimizing the influence of technical scanner and protocol variations 6 is not strictly necessary.
Various studies investigated the correlation between PDAC enhancement in CT and the presence and degree of prognostically relevant histopathological tumor features.A prognostically unfavorable weak PDAC enhancement was associated with the negative prognostic factors high tumor cellularity, high histopathological grading, and tumor necrosis 14,[25][26][27] .However, the relationships between other histopathological features, CT enhancement, and clinical endpoints are more complex.Low late arterial tumor enhancement which was a negative prognosticator in the present and previous studies 23,28 was associated with the beneficial prognostic markers low microvessel density and high content of fibrotic stroma 23,25,29 .Abundant stroma, though, was also linked to high portal venous tumor enhancement (positive prognosticator) 13 .
A relevant proportion of enhancement formulas analyzed in the present study (formulas ( 15)-( 23)) incorporate both tumor enhancement and enhancement of the non-neoplastic parenchyma.A landmark renal cell carcinoma study where enhancement normalization to "normal" renal parenchyma (and the aorta) improved tumor characterization is often mentioned as a rationale for tumor enhancement normalization 19 .In the pancreas of PDAC patients, however, the non-neoplastic parenchyma is by no means "normal".It is characterized by varying degrees of chronic inflammation and fibrosis both of which are independently associated with a poor prognosis 30 .In the present study, formulas evaluating the enhancement of the (whole) tumor to the non-neoplastic parenchyma (formulas ( 15)-( 19)) yielded no relevant prognostic information.In line with this, in a study by Vyas et al., the absolute tumor attenuation (1), but not the tumor attenuation normalized to the non-neoplastic parenchyma in the late arterial phase (18) was predictive of survival in PDAC patients after pancreaticoduodenectomy 28 .One major limitation of most studies incorporating the non-neoplastic pancreatic parenchyma into their enhancement formula is the lack of differentiation between or pooling of upstream and downstream parenchyma 6,16,17,28,[31][32][33] .In the present and a previous study, downstream parenchyma behaved similarly to the healthy pancreas with an enhancement peak at the late arterial phase 34 .This early peak is usually absent in the upstream parenchyma, possibly due to a higher degree of fibrous parenchymal replacement 34 .Therefore, in the present study, we avoided pooling upstream and downstream parenchyma but performed all analyses of the non-neoplastic parenchyma using solely upstream parenchyma (downstream parenchyma was available in fewer patients).
In our study, attenuation values of the non-neoplastic parenchyma were not age-dependent which is in contrast to a study by Itoh et al. 35 .We did, however, observe higher tumor enhancement values in above median age patients (( 2), ( 4), ( 7), ( 11), ( 14), ( 18)) although the biological basis of this finding is not clear.Some of the analyses in our study put a particular focus on the enhancement of the peripheral tumor parts or the interface of tumor and non-neoplastic parenchyma (formulas ( 20) -( 23)).Biologically, the tumor periphery differs from the tumor center in terms of MVD, stroma content, and cellular density, all of which potentially influence enhancement 36,37 .In a few previous studies, high attenuation differences between the peripheral tumor parts and non-neoplastic parenchyma ("high delta") were associated with adverse histopathological features (e.g.lymphovascular invasion) and poor clinical outcomes (e.g.high risk of recurrence) 16,32,33 .In our study, "high delta" tumors had no elevated risk of recurrence compared to "low delta" tumors which might be explainable by a potentially high variability in interpretation of the tumor margin 38 .
The present study only included PDAC patients after upfront surgery to generate a clinically more homogeneous patient dataset.As PDAC is increasingly seen as systemic disease, irrespectively of the initial stage, there currently is a paradigm shift in the management of initially resectable PDAC towards neoadjuvant therapy (NAT) which might improve TTR and OS in some patients 39 .Future radiology (enhancement) studies could help to identify patients with initially resectable PDAC that could profit from NAT.
In recent years, the proportion of radiology PDAC studies using Radiomics and Artificial Intelligence (AI) for postoperative prognosis estimation has been increasing.They often have a multicentric design which facilitates the inclusion of larger patient numbers 40,41 .The majority of these studies on PDAC rely on manual three-dimensional image segmentations to enable imaging feature extraction 41 .Some groups, however, recently managed to develop reliable automated (deep) segmentation and prognostic models which increases scalability and makes near-term translation into routine radiological practice more realistic 40 .Similar to the enhancement formula studies, several Radiomics/AI models also include information from the non-neoplastic parenchyma as well as clinical parameters for improved prognosis prediction 41 .Compared to the best-performing enhancement formulas, the prognostic capability of most Radiomics/AI models is still in the same range but is continuously improving 40,41 .
As shown in the present and previous studies, PDAC has a high but variable risk of recurrence after surgical tumor resection 5,8 .Insufficient information on the risk of recurrence can lead to patient anxiety and manifest PDAC recurrence is associated with a particularly high deterioration in health-related quality of life 42 .On a patient level, prognostic imaging markers such as the enhancement formulas from the present study and Radiomics/AI models could be a step in the direction toward more individualized PDAC surveillance programs after curative resection and more personalized treatment approaches to PDAC 43 .
Most guidelines, such as the National Comprehensive Cancer Network guideline, allow some flexibility regarding the frequency of follow-up CT scans (e.g.every 3-6 months for two years) 10 and patients with a high recurrence risk (determined from risk assessments such as in the present study) could possibly profit from more frequent imaging (every 3 months).However, more data on the clinical benefit and cost-effectiveness of detection of recurrence at an early stage are desirable.Some older studies reported that routine postoperative imaging is not cost-effective as it might not have a significant impact on survival 44 , especially in patients with a poor performance status that are not fit for treatment of their recurrence 45 .Yet, there are more positive studies on imaging surveillance, such as a nationwide Dutch cohort study which inferred that postoperative surveillance with CA 19-9 and radiologic imaging has the potential to improve survival 46 .An ongoing international randomized controlled trial will provide further high-quality evidence on the clinical benefit and cost-effectiveness of a recurrence-focused surveillance (CA 19-9 & CT every three months) versus non-standardized surveillance (CA 19-9 & imaging only in case of symptoms) 47 .
There are some limitations to our study.First, we used TTR as the sole time-to-event endpoint since many patients were still alive at the end of follow-up.Second, the transferability of the findings from a single-center study might be limited.We did, however, include many external CT scans which added diversity to our CT dataset.Third, we did not perform image normalization prior to enhancement analyses because we wanted to keep the analyses technically simple and easy to repeat.Although we detected no or weak correlations between CT acquisition/ reconstruction parameters and enhancement measurements as well as TTR values, we cannot exclude that the technical variability had an influence on our results.Forth, the sample size of our study was moderate.Future larger (prospective) multi-center studies are desirable for an improved power of statistical analyses.Fifth, as this is an exploratory study and we wanted to avoid a high rate of false-negative findings, no alpha adjustment was done 48,49 .However, with this approach, one must be aware of an increased chance of false-positive findings in our studies.Thus, the positive findings from our exploratory study should be tested in future confirmatory studies.
In summary, our study identifies several CT enhancement formulas that have a prognostic ability to predict tumor recurrence in PDAC patients after upfront resection.Almost all of the best-performing formulas measure solely tumor tissue without any normalization to non-tumor structures.Among these top performers were the absolute tumor attenuation values in the late arterial and portal venous phase.The tumor attenuation can be easily measured on routine preoperative CTs and thus is more readily available than histopathological prognostic markers such as grading and lymph node metastasis which are difficult to determine preoperatively.Improved prediction of tumor recurrence could be beneficial for personalized surveillance protocols and treatment strategies.

Materials and methods
The present retrospective study on CT enhancement of PDAC patients to predict TTR after upfront surgery was approved by the ethical committee of Heidelberg University, Germany (S-711/2021).The experimental protocol (including the retrospective search for patients in the local radiological database, pseudonymized export of CT files, placement of ROIs in CTs, and correlation of CT attenuation/enhancement values with prognostic and histopathological parameters) was approved by the ethical committee of Heidelberg University.Informed consent was waived in accordance with the data protection law of Baden-Württemberg § 13 by the ethical committee of Heidelberg University since obtainment of informed consent would have entailed a disproportionately high effort.
The present study is an exploratory study and not a confirmatory study of previously published results since most previous studies on CT enhancement quantification of PDAC used different endpoints (Supplementary Table 1).
The CT scanning protocols varied (see Supplementary Materials page 21).
The following biochemical and clinical parameters were collected and analyzed for all patients: age, sex, histopathological diagnosis, radiological tumor size, TNM stage (8th edition), histopathological grading, UICC stage, serum levels of tumor markers CA19-9, and CEA, pancreas resection (date, type), date of recurrence, type of recurrence, date of last follow-up.
TTR was defined as the time from surgery to detection of locoregional recurrence and/or distant metastases on follow-up CT scans.The imaging definition of tumor recurrence is described in the Supplementary Materials (page 3).

Image analysis of the preoperative CT scan
Image analyses were performed by two board-certified radiologists in consensus, who were blinded to the patients' outcomes, using a free and open-source code software (Horos (LGPL-3.0)).After coregistration of the axial images of the triple-phasic CT examination, the pancreatic tumor was identified, the slice with the maximal tumor dimension was selected, and ROIs were placed in the tumor, non-neoplastic parenchyma, and the aorta (Fig. 1 and Supplementary Materials (page 3)).ROIs were copied between each phase.Hounsfield Units (HU) were extracted from each ROI in each phase.

Enhancement studies/formulas
The PubMed ® MEDLINE and PubMed Central ® search for identification of CT enhancement studies is described in the Supplementary Materials (page 4).
Power size calculation for TTR analysis was conducted.Previously reported Hazard Ratios (HRs) of CT enhancement measurements for prediction of tumur recurrence ranged between 1.96 and 7.1 and were used as a basis for the analysis 13,16,31 .Assuming HR = 1.96, α two-tailed = 0.05, β = 0.2 (power = 0.80), an even distribution of groups (median as cutoff value), a baseline event rate of 0.59 (events/year = 1-year recurrence rate from Li et al. 41 ), and a follow-up until recurrence or for ≥ 2 years, a sample size of 87 patients is required.
Mann-Whitney-U test and Wilcoxon Test were used to compare continuous variables between independent and paired samples.ANOVA with one-way analysis of variance was used to test differences between means of subgroups of a variables.Chi-squared Test was used to compare categorical variables between groups.Spearman's correlation coefficient was obtained to define the correlation between continuous variables.TTR analysis was performed using Kaplan-Meier analysis and log-rank test as well as Cox proportional hazard regression analysis.In univariate Cox regression analysis, the ENTER method was used.For multivariate Cox regression analysis, variables were entered sequentially (FORWARD method) if their associated significance level was < 0.05 and variables were removed if their associated significance level was > 0.10, or all variables were entered in the model in one single step (ENTER method).Harrell's C-indices were computed and compared for Cox models.ROC curve analysis was performed to evaluate the discriminatory ability of continuous and ordinal variables for the correct assignment of cases into cases without and with tumor recurrence at 1 year after surgery.Standard errors of AUC values and differences between two AUC values were calculated using the DeLong method.
In the present exploratory study, no alpha adjustment for multiple testing was done, as suggested by Bender & Lange 48 and Althouse 49 .Alpha adjustment would increase the rate of false-negative findings (type II error), meaning that true correlations between enhancement values and clinical variables could be missed.However, using this approach, there is an increased chance of false-positive findings.Therefore, the positive findings (p < 0.05) from the present study should be tested in future confirmatory studies 48 . https://doi.org/10.1038/s41598-024-70441-3

Figure 1 .
Figure 1.Placement of regions of interest (ROIs).Shown are the ROIs in a patient with a PDAC in the pancreatic head in the (a) non-contrast, (b) late arterial, and (c) portal venous phase; CT acquired in an oblique, 30°, right-sided down position 20 .Blue ROI tumor: oval/round, centered in the middle of the tumor, with a margin of at least 2 mm to the border of the tumor.Green ROI tumor periphery: freehand, approximately 5 mm thick, peripheral tumor part.Yellow ROI upstream parenchyma-border to tumor: freehand, upstream parenchyma directly adjacent to the tumor.Orange ROI upstream parenchyma-best measurable: oval or freehand, best measurable area of upstream non-neoplastic tissue.Red ROI aorta: oval/round, in the aortic lumen, diameter ~ 15 mm.

Table 1 .
Demographic & clinical data and CT enhancement values in patients without and with tumor recurrence within 1 year.art late arterial, CA19-9 carbohydrate antigen 19-9, HU Hounsfield units, IQR interquartile range.M metastasis, N nodal, nc non-contrast, ven portal venous, T tumor, Tu tumor.Significant values are in bold.
Tu ven − Tu nc

Table 2 .
Univariate Cox regression analyses: enhancement as a predictor for tumor recurrence.art late arterial, CI confidence interval, nc non-contrast, ven portal venous, T tumor, Tu tumor Upstream upstream parenchyma.Significant values are in bold.